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wav2vec2-rapnic-example-google-colab – AI Model by 007arbab | AlphaNeural AI
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007arbab
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wav2vec2-rapnic-example-google-colab
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transformers
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
facebook/wav2vec2-base
finetune
apache-2.0
endpoints_compatible
us
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wav2vec2-rapnic-example-google-colab
This model is a fine-tuned version of
facebook/wav2vec2-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.1076
Wer: 1.0876
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 30
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
7.7457
9.6154
500
3.0582
1.0
2.9104
19.2308
1000
2.3466
1.0
1.3678
28.8462
1500
2.1135
1.0742
1.3678
30.0
1560
2.1076
1.0876
Framework versions
Transformers 5.12.1
Pytorch 2.11.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2
